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FAQ
actinia does not send a completion signal by default, but a webhook can be used to receive a notification when processing has finished.
Creating or editing a shared data pool through the API is generally not recommended.
By design, the persistent database is not editable through the API and is often mounted as read-only to help prevent data loss. Depending on the deployment, there are several options:
- In a basic Docker deployment, the data storage may be mounted and edited directly with GRASS GIS.
- In a Kubernetes deployment or similar environment, the data pool can be created with an init container. An example is available in the actinia Helm chart.
- Mapsets are shared among groups. If all relevant users belong to the same group, the API can be used to edit the user database.
actinia 's uniqueness lies in its cloud-based, open source REST API that enables scalable and distributed high performance processing of geospatial data. Its integration with GRASS GIS and GDAL for computational tasks and its ability to process a wide range of geospatial data, including satellite imagery and time series, sets it apart. Its modular design with plug-ins for various functionalities such as metadata catalogue management and parallelization further enhances its advantages.
A person should choose actinia for its:
- High scalability and performance in cloud environments.
- Open source nature, providing flexibility and community support.
- Advanced geospatial processing capabilities, including satellite image processing and time series analysis.
- Modular architecture that allows for customised deployments.
- Integration capabilities with Jupyter Notebooks and Hub for ease of use in data science workflows.
The primary audience for actinia includes
- Companies, organisations and institutions requiring advanced geospatial processing capabilities in cloud environments.
- Professionals working with satellite imagery and geospatial data.
- Geospatial and Earth observation analysts and scientists.
- Developers and engineers looking for a scalable, cloud-based geospatial processing platform.
The story behind actinia revolves around the need for a scalable, efficient, and flexible platform for processing complex geospatial data in the cloud. Originally developed by Sören Gebbert and mundialis (Germany) in 2017 in the wake of high-quality data from the Copernicus program, it has since evolved into a tool that also addresses data offerings from New Space satellite sensors. Actinia aims to harness the power of cloud computing and open source software to bring advanced geospatial processing capabilities to a wide range of users. It is a community project of the Open Source Geospatial Foundation (OSGeo.org).
The primary technologies used in building actinia include:
- actinia is written in Python.
- actinia uses mainly GRASS GIS and GDAL for geospatial data processing.
- for deployment, cloud computing technologies are used for scalability and distributed processing.
- REST API for easy integration and accessibility.
- various actinia plugins for extended functionalities like OGC-CSW, STAC support, and parallel processing techniques.
While specific customer names are not provided, actinia 's biggest customers are:
- Large corporations in sectors like telecommunication, supply chain management, urban planning, and environmental management that rely on geospatial data.
- Tech companies and startups needing a robust, scalable platform for geospatial data processing in their products or services.
- International, governmental and environmental agencies requiring advanced geospatial data analysis.
- Research institutions and universities engaged in geographical and environmental studies.